checkPredict function

Prevention of numerical instability for a new observation

Check that the new point is not too close to already known observations to avoid numerical issues. Closeness can be estimated with several distances.

checkPredict(x, model, threshold = 1e-04, distance = "euclidean", type = "UK")

Arguments

• x: a vector representing the input to check, alternatively a matrix with one point per row,
• model: list of objects of class km, one for each objective functions,
• threshold: optional value for the minimal distance to an existing observation, default to 1e-4,
• distance: selection of the distance between new observations, between "euclidean" (default), "none", "covdist" and "covratio", see details,
• type: "SK" or "UK" (default), depending whether uncertainty related to trend estimation has to be taken into account.

Returns

TRUE if the point should not be tested.

Details

If the distance between x and the closest observations in model is below threshold, x should not be evaluated to avoid numerical instabilities. The distance can simply be the Euclidean distance or the canonical distance associated with the kriging predictive covariance k:

The last solution is the ratio between the prediction variance at x and the variance of the process. none can be used, e.g., if points have been selected already.